A Changing Landscape
The Need for an Ecological Approach to Building Start-ups
This chapter is a part of the book “How to Build Thriving Start-up Ecosystems: Five Information Patterns for Success.”
There is a sort of mythology of the start-up founder as a lone visionary (generally a man) that toils away in his garage, seeing a future no one else can. This myth has always ignored much of the ecosystem of investors, mentors, and collaborators around the founder that made their trajectory possible, even if it does make for a compelling story.
As the startup ecosystem globalizes and AI accelerates corporate consolidation, clinging to the myth of the lone visionary risks undermining innovation when collective effort is needed most. To maintain its position as the epicenter of global innovation, the United States must adopt an entrepreneurial narrative that emphasizes the power of ecosystems — where investors, mentors, collaborators, and diverse teams work together to foster sustainable growth.
Is Entrepreneurship Worth Saving?
The numbers of founders that start small businesses like restaurants, hair salons, and landscaping businesses has declined since the middle 1980’s while the rate of people starting potentially scalable start-ups has increased over the last two decades. However, while more people are now trying to start scalable ventures, fewer of these potential companies now succeed. Where in the last two decades one out of ten start-ups were expected to succeed, today this number has dropped to one in twelve (Failory). While the average American likely cares little for the success of an economic sector outside of their control, the dynamism of the start-up ecosystem has ripple effects on labor productivity and income inequality that impacts American society as a whole.
The flagging rate in both more predictable business creation and start-up success is worrisome because small businesses and start-ups represent an outsized contribution to positive job growth compared to older companies. Start-ups are also responsible for an outsized portion of positive labor productivity, which has decreased from 2.2% in the previous five decades to a .9% annual growth rate today. The labor productivity rate is a good indicator for increased standard of living. A slow increase in labor productivity means that people are not seeing a future that is markedly better than their past. Start-ups are “disproportionally responsible for truly radical innovations — the airplane, the railroad, the automobile, electric service, the telegraph and telephone, the computer, air conditioning” (Litan). Without new start-ups, the future feels the same as the past.
Start-up success rates impact income inequality both directly and indirectly. The more equitable a society’s wealth distribution, the lower its social unrest, unemployment, and improved overall economic growth (Dabla-Norris). Start-ups reduce income inequality directly when founders offer equity compensation which enables people from all income levels to benefit from a company’s growth (Kauffman). Start-ups indirectly decrease income inequality by disrupting traditional monopolies. Disrupting monopolies has positive ripple effects for consumers, with start-ups boosting affordability and choice via competition. Uber and Lyft disrupted the taxi industry to make taxis more convenient and affordable for people (until they became the incumbents) (Wallsten). Netflix and Spotify disrupted entrenched media companies to provide lower-cost entertainment options.
Start-ups are also highly adaptable to changing environments; in a world that faces climate change and globalized pandemics, a high rate of start-ups enables the economy to be more adaptable and resilient to rapidly changing market conditions (Friedman).
Even for people that work far outside of the start-up ecosystem, the research is clear: high rates of start-up creation helps everyone.
David Is Now Owned by Goliath
One of the reasons for entrepreneurship’s decline is due to the nature of today’s entrepreneurship. Many of today’s start-ups rely on platforms where incumbents have the advantage of powerful network-effects where each additional user makes the product or service more valuable to all other users. This makes it harder for new entrants to compete since it is harder for them to add greater value (Surowiecki).
Many new products are even built on the platforms of large incumbents, making it hard for start-ups to challenge the bedrock on which their codebases and marketing channels are derived. Few start-ups can tackle a new way to search when people are likely to find out about their platform on Google, and not many start-ups can build a new kind of app store when the Apple and Android stores come pre-loaded on people’s phones. This makes radical shifts — -an entirely new way to search, new paradigms of thinking what an app can be, communication devices outside of phones — -hard for founders to even imagine or explore.
Easier to Start, Harder to Scale
Investors also increasingly expect founders to generate revenue before providing any investment. This is in part because many of the splashiest tech companies of the last economic cycle, from WeWork’s failed IPO, Uber and Lyft’s lack of profit, BlueApron’s rapid decline in stock value, and Peloton’s struggling user rates after the pandemic, have left investors with lackluster returns and in turn more reticent to part with their funds. Investors now want a clearer path to profitability, and put the onus on founders to find this path before they get money.
Rising interest rates over the course of 2022 to 2024 have also impacted the market, making it harder for tech founders to borrow and seeing angel investors shift towards more certain investments such as bonds (Schmidt).
This funding climate has left founders with an increasingly large gap in funds between when they start a companies to the point at which they obtain investment. Only those with personal savings to pay for rent, healthcare, and technology development costs can cross this gap. With net worths decreasing against inflation across ninety-nine percent of the U.S. population, this means fewer people are able to make this leap.
A Widening World
At the same time as America grapples with concentrated wealth and changing investment strategies, international shifts in investment flows have made American founders suddenly need to compete with other founders globally. Nations around the world have invested in creating attractive cities and have begun to develop targeted investment funds to retain potential founders, which has meant fewer founders relocating to the United States to get their big break (Florida).
China especially has emerged as a major venture capital player, with a 375% increase in venture capital spending over the last decade to bring them from 4% of venture capital investment in 2005 to a quarter of investment in 2017 (Florida). These investments are increasingly being put into Chinese, rather than American start-ups.
AI Comes to the Fore
AI has shifted the economy faster than perhaps any other technology in history. It has enabled the automation of routine emails, blog posts, logistics, data processing, art, graphic design, AI voice overs, and customer service chatbots (De Cremer). This has in turn created a steep drop in work for many customer service reps, artists, voice actors, writers, and editors in a matter of months. At the same time AI demand has created or increased the roles of data scientists, AI/ML engineers, AI prompt developers, and AI ethics professionals. The rise of AI has created a rapid polarization in the market, with many creative and administrative jobs suddenly disappearing to be replaced by smaller numbers of AI specialists. This has created ripple effects on industries outside of tech as creative professionals quickly move to other fields (Ellingrud).
For the start-up ecosystem, the emergence of AI has enabled a single founder to move further, faster, with the help of AI tools that can help them bring a product to market faster, auto-generate content needed for Search Engine Optimization, and automate emails to potential investors. AI has been the magic word that has opened up investor wallets even in a time of high interest rates. In 2023, it was 25.9 billion for the full year, which was a 200% increase from the 92 billion invested in AI in 2022 (Bloomberg). In the first six months of 2024, investors have put 26.8 billion dollars into 498 generative AI deals, already surpassing their investment dollars of the year before.
So many investors are rushing to fund AI start-ups because a pivotal component of the strength of AI models is data. A start-up that has vastly more data than another will likely have more accurate models, leading to more people using it, which enables it to collect even more data in a perpetual cycle. AI presents a huge first-mover advantage that makes a future scenario where everyone uses the same two or three corporations’ AIs a strong possibility. Since AI models come with the biases of the data put into them, having two or three corporate AIs involved in the majority of the world’s repetitive white collar tasks leads to the potential of a world where current biases on hiring, investment decisions, mortgage lending, and many other decisions are increasingly codified and reinforced with the power of AI.
Past the Lone Founder Mythology
Keeping the ideal of the lone founder as the dominant mythology of the American entrepreneurial ecosystem will likely see AI continue to agglomerate around two or three large corporations and investment increasingly flow to ecosystems outside of the country. An ecological view of entrepreneurship that embraces the systems around a founder’s success is a huge step towards expressly building the systems that will be needed to help founders in the United States compete in this new start-up landscape.
Traditionally an ecosystem perspective of entrepreneurship has meant accelerators, co-location near large tech firms, and tech investment firms. These support systems are often slow to create or procure, expensive to maintain, and hard to replicate within most of the country. This book’s goal is to present a more nimble way to provide a supportive entrepreneurship ecosystem. It does this first by breaking down the mental processes that a founder goes through to start and scale a company into repeatable patterns. It will then look at how these processes can be replicated in faster, cheaper ways that traditional models that can enable a wider range of entrepreneurs to gain support.
